Customer Service
Complaint triage and first-draft response
Classify incoming complaints by type and urgency, then generate a first-draft response. Agent reviews, personalises, and sends. Faster turnaround, consistent tone.
40–60%
reduction in average handling time
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Very easy to implement. Ready-to-use tools exist. Can be up and running in days or weeks with minimal technical resource.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
Klarna's AI assistant handled 2.3M conversations in its first month — two-thirds of all chats — doing the work of 700 full-time agents. Resolution time dropped from 11 minutes to under 2 minutes, with an estimated $40M profit improvement (Klarna).
Agent review before sending is non-negotiable — particularly for complaints with legal, safety, or reputational sensitivity.
Define the classification taxonomy first (complaint types, urgency levels, routing rules) — the AI applies your framework, it doesn't create one.
Train agents on how to work with AI drafts rather than starting from scratch: the habit shift is the main change management task.
Track two metrics from day one: agent acceptance rate (percentage of AI drafts sent with minimal edits) and customer satisfaction. If acceptance falls below 50%, the prompt or taxonomy needs work before scaling.
Experiment starter: Identify your three highest-volume complaint types. Use an LLM to classify and draft responses for 100 historical complaints of those types. Have agents rate the drafts blind. If 70%+ are rated usable with light editing, run a live pilot on those complaint types only.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation opportunity — see the relevant playbook section for how to approach it.More in Customer Service
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Return reason categorisation
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AI Transformation Playbook
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